On 27.06.2015 18:08, kenanh wrote:
> Hi,
>
> I'm loading directed weighted graph from csv file into graph-tool graph
> graph. The organization of the input csv file is:
>
> 1,2,300
> 2,4,432
> 3,89,1.24
> ...
>
> Where the fist two entries of a line identify source and target of an edge
> and the third number is the weight of the edge.
>
> Currently I'm using:
>
> import csv
> g = gt.Graph()
> e_weight = g.new_edge_property("float")
> f_network = open(in_file_directory+ '/'+network_input, 'r')
> reader_network = csv.reader(f_network, delimiter=delimiter)
> for edge in reader_network:
> e = g.add_edge(int(edge[0]), int(edge[1]))
> e_weight[e] = float(edge[2])
> f_network.close()
>
> However it takes quite long to load the data (I have network of 10 millions
> of nodes). I have tried to make it faster by using g.add_edge_list, but this
> works only for unweighted graphs. Any suggestion how to make it faster?
Yes, use g.add_edge_list() for the edges, and put the weights separately
via the array interface for property maps:
e_weight.a = weight_list
The weight list should have the same ordering as the edges you passed to
g.add_edge_list().
Best,
Tiago
--
Tiago de Paula Peixoto <[email protected]>
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